Noise removal system

ABSTRACT

A system for noise removal is coupled to a signal unit that provides a digital signal. The noise removal system includes a transformation module to transform the digital signal into an f-digital signal, a threshold filter to generate a noiseless signal from the f-digital signal based on a threshold profile, and a signal synthesizer to provide a gain to the noiseless signal and to transform the noiseless signal into an output signal.

RELATED APPLICATION

The present application is a continuation of U.S. patent applicationSer. No. 12/766,210, filed Apr. 23, 2010 and claims priority of Indiapatent Application No. 2606/DEL/2009 filed Dec. 15, 2009, both of whichare incorporated herein in their entirety by this reference.

FIELD OF THE INVENTION

The present invention relates to noise removal systems and moreparticularly to active noise removal systems for removal of backgroundnoise which otherwise can distort signals processed and/or measured byelectrical appliances.

BACKGROUND

A variety of appliances, such as mobile phones, set-top boxes,electrocardiogram (ECG) monitors, and music systems suffer from noise,due to which a useful signal gets distorted. Background or ambient noiseis generally controlled using noise removal systems. Noise removalsystems can include an active noise removal system, such as an activenoise cancellation (ANC) system, and a passive noise removal system.While passive noise removal systems use unpowered techniques, such asinsulation or sound absorbing ceiling tiles or mufflers, the activenoise removal systems use powered systems for the removal of thebackground noise.

The active noise removal systems generally include an analog-to-digitalconverter (ADC) due to which quantization noise is also introduced in adigitized output signal. Quantization noise is the difference between anactual value of an analog input signal and the corresponding digitizedoutput signal. Generally, different techniques, such as oversampling anddithering, are used to reduce the quantization noise. However, suchtechniques are usually inefficient and also result in a loss of signalreliability. Further, in an ANC system, generally an anti-noise signalhaving the same amplitude, but an opposite phase to that of the noisesignal is used to cancel the noise signal. However, this leads to a lossof fidelity and overall signal energy.

SUMMARY

This summary is provided to introduce concepts related to a noiseremoval system, which are further described below in the detaileddescription. This summary is not intended to identify essential featuresof the claimed subject matter, nor is it intended for use in determiningthe scope of the claimed subject matter.

In an embodiment, the system includes a signal unit for providing adigital signal and a noise removal system coupled to the signal unit.The noise removal system includes a transformation module configured totransform the digital signal into an f-digital signal, a thresholdfilter configured to generate a noiseless signal from the f-digitalsignal based on a threshold profile, and a signal synthesizer configuredto provide a gain to the noiseless signal and to transform the noiselesssignal into an output signal.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is provided with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Thesame numbers are used throughout the drawings to reference like featuresand components.

FIG. 1 illustrates an electronic system implementing an exemplary noiseremoval system, according to an embodiment of the present subjectmatter.

FIG. 2 illustrates the exemplary noise removal system, according toanother embodiment of the present subject matter.

FIG. 3A shows a snapshot of a noisy multi-tone signal in time domain.

FIG. 3B represents a frequency spectrum of the noisy multi-tone signal.

FIG. 3C represents a snapshot of the noisy multi-tone signal in timedomain after it is processed by the exemplary noise removal system ofFIG. 2.

FIG. 3D illustrates an error between a noisy multi-tone signal of FIG.3A and the output signal represented in FIG. 3C.

FIG. 4 illustrates an exemplary noise removal system, according to yetanother embodiment of the present subject matter.

FIG. 5A illustrates an 18-bit leaky tone signal in the frequency domain.

FIG. 5B illustrates the frequency domain plot of a noiseless signalgenerated by the noise removal system of FIG. 4.

FIG. 5C represents an error plot of an output signal with respect to anideal 20-bit time domain signal.

FIG. 6 illustrates an exemplary method for implementing a noise removal,in accordance with an embodiment of the present subject matter.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Systems and methods for noise removal are described herein. Inparticular, the systems and methods remove noise from a signal andprocess the signal to improve dynamic headroom. These systems andmethods can be implemented in a variety of electronic and communicationdevices, such as set-top boxes, mobile phones, monitors, music systems,and automobiles.

In one implementation, a digital signal suffering from background noiseand quantization noise is transformed into a frequency-domain digitalsignal. The frequency-domain digital signal includes bins correspondingto both the useful signal and the noise signal. To remove noise, thebins corresponding to the noise signal (also known as noise bins) areremoved from the frequency-domain digital signal, based on an amplitudethreshold value. The amplitude threshold value can be either dynamic orstatic. The remaining bins, i.e., the bins corresponding to the usefulsignal (also referred to as useful bins), are processed to occupy adynamic headroom created due to the noise removal. Such processing helpsin improving fidelity of the digital signal. Further, the system may beconfigured to create an output signal with greater dynamic range andprecision than an analog input signal while removing both background andquantization noise.

FIG. 1 illustrates a system 100 implementing an exemplary noise removalsystem 102, according to an embodiment of the present subject matter. Itwill be understood that any number of the described system blocks can becombined in any order to implement the system 100, or an alternatesystem. Additionally, individual blocks may be deleted from the system100 without departing from the scope of the present subject matter. Thesystem 100 can be implemented in any suitable hardware, software,firmware, or a combination thereof.

The system 100 includes a noise removal system 102, a signal unit 104,and a digital signal processor (DSP) 106. In an embodiment, the signalunit 104 includes a receiver 110, an analog-to-digital converter (ADC)112, and a pre-processing unit 114. The receiver 110 receives an analoginput signal 116 from an external source such as a microphone (not shownin this figure). The analog input signal 116 may be an audio signal, avideo signal, or a data signal, which may suffer from background noise.Background noise is any unwanted signal associated with the usefulsignal.

The receiver 110 transfers the analog input signal 116 to the ADC 112.The ADC 112 samples the received analog input signal 116 and assigns adiscrete value or bit to each sample of the analog input signal 116 toprovide a digital signal. The digital signal thus generated is usuallynoisy and is a combination of useful bits and noise bits. Some of thenoise bits in the noisy digital signal correspond to the backgroundnoise in the analog input signal 116. Additional noise bits may getintroduced in the noisy digital signal due to quantization noise inducedduring analog-to-digital conversion. Quantization noise is thedifference between an actual analog input value corresponding to voltageor current of an input signal and a quantized digital value. Thequantized digital value in turn is the digital equivalent of the analoginput value and is provided by an ADC, such as the ADC 112.

The noisy digital signal thus generated can be of N-bits where the valueof N depends on the configuration of the ADC 112, as will be understoodby a person skilled in the art. For example, a 16-bit ADC can generate a16-bit digital signal. Examples of the ADC 112 include, but are notlimited to, a sigma-delta ADC, a successive approximation ADC, a flashADC, etc.

In one embodiment, the signal unit 104 may be configured to directlyprovide the noisy digital signal to the noise removal system 102 withoutany pre-processing. In another embodiment, the digital signal 108 can beprovided to the noise removal system 102 after pre-processing of thenoisy digital signal for preliminary noise removal.

For the purpose of preliminary noise removal, the noisy digital signalmay be fed to a pre-processing unit 114. The pre-processing unit 114 mayinclude adders or subtractors as illustrated in the subsequent figures.In one implementation, the pre-processing unit 114 cancels backgroundnoise by subtracting an equivalent noise from the noisy digital signalto yield a digital signal 108. Further, the digital signal 108 is fed tothe noise removal system 102. In another implementation, in order toreduce quantization noise, the pre-processing unit 114 adds a dithersignal to the noisy digital signal to yield the digital signal 108. Thedigital signal 108 is then fed to the noise removal system 102.

In an embodiment, the noise removal system 102 includes a transformationmodule 118, a threshold filter 120, and a signal synthesizer 122. Thetransformation module 118 receives the digital signal 108 and transformsit from time domain to frequency domain. The transformed signal infrequency domain is hereinafter referred to as f-digital signal 124.

In order to generate the f-digital signal 124, the transformation module118 determines the number of frequency coefficients associated with thedigital signal 108. The frequency coefficients represent amplitudes of apre-defined number of frequency samples or frequency points. In oneimplementation, the number of frequency coefficients can be determinedbased on techniques used for the transformation and on the intendedapplication of the f-digital signal 124. Examples of such techniquesinclude, but are not limited to, Fast Fourier Transform (FFT), DiscreteCosine Transform (DCT), and Discrete Wavelet Transform (DWT).

Typically, two frequency samples are chosen to represent a frequencyrange that contains energy in the form of a voltage. The frequency rangeis hereinafter referred to in terms of a frequency bar or frequency bin.A number of such frequency bins represent a frequency spectrum of thedigital signal in the form of the f-digital signal 124.

As mentioned before, the digital signal 108 is a combination of usefulbits and noise bits. Similarly, the f-digital signal 124, which is afrequency domain transformation of digital signal 108, also includes acombination of useful bins and noise bins. The noise bins, like thenoise bits, correspond to the background and quantization noise. Thetotal energy in the frequency spectrum of a particular f-digital signal124 is thus distributed over the useful bins and the noise bins. Such anf-digital signal is fed to the threshold filter 120. Alternatively, thef-digital signal 124 may be first optimized using a signal optimizer(not shown in the figure), which removes background noise based on aknown noise profile of the background noise. The optimized f-digitalsignal may then be provided to the threshold filter 120.

The threshold filter 120 refines the f-digital signal 124 by removingthe noise bins based on a threshold profile. In an implementation, thethreshold profile can be an amplitude threshold value for the f-digitalsignal 124. The amplitude threshold value can either be pre-set in thethreshold filter 120 or can be calculated dynamically by the thresholdfilter 120. In an implementation, the threshold filter 120 can remove orpurge the bins having amplitude values below the amplitude thresholdvalue and select the bins having amplitude values above the amplitudethreshold value to get rid of the noise bins. The removal of the noisebins refines the f-digital signal 124 to generate a noiseless signal126. Additionally, removal of the noise bins also leaves a dynamicheadroom in the noiseless signal 126, which is then fed to the signalsynthesizer 122.

The signal synthesizer 122 increases a gain of the received noiselesssignal 126 so that the dynamic headroom in the noiseless signal 126 getsoccupied. For example, in case an FFT is used to transform the digitalsignal 108 to the f-digital signal 124, the gain of the noiseless signal126 can be increased by increasing the number of FFT frequency samplesor, simply, FFT points. In another implementation, the dynamic headroomcan be occupied by providing the gain to the noiseless signal 126 suchthat the gain is proportional to the total energy lost in the removedbins.

Thus, the signal synthesizer 122 provides an increased gain noiselesssignal, hereinafter referred to as f-recovered signal. The signalsynthesizer 122 can also be configured to reconstruct the f-recoveredsignal in time domain to yield an output signal 128. The output signal128 in time domain can be obtained using a variety of techniques, suchas inverse FFT, inverse DCT, and inverse DWT, as known in the art.

The output signal 128 is generated such that it can accommodate theextra bits generated due to the gain or amplification by the signalsynthesizer 122. For example, an f-recovered signal can be boosted toprovide a 20-bit output signal 128 when the ADC 112 was originallyconfigured to generate an 18-bit output signal 128. Examples of thesignal synthesizer 122 include, but are not limited to, a phase lockedloop (PLL) frequency synthesizer, a direct digital synthesizer, adigiphase synthesizer, a sine generator, a cosine generator, etc.

The output signal 128 can be sent to a digital signal processor (DSP)106 to further process the output signal 128 by using a variety oftechniques known in the art, such as filtration, amplification, andmodulation, to provide a processed signal 130. The processed signal issubstantially free from the background noise and the quantization noise,and can be used for a variety of applications. In an implementation, theprocessed signal 130 can be applied to an amplifier to drive a speaker(not shown in this figure) to receive a reliable voice output. The noiseremoval system 102 has been shown as a component separate from the DSP106. However, it will be understood that the noise removal system 102can be included in the DSP 106 in a different embodiment.

FIG. 2 illustrates the exemplary noise removal system 102, according toanother embodiment of the present subject matter. By way of an example,the noise removal system, such as the noise removal system 102, has beenexplained hereinafter as part of an audio processing system 200, such asone used in mobile phones. However, it will be understood that the noiseremoval system 102 can be implemented in a variety of systems used fordifferent applications.

The audio processing system 200 includes multiple microphones 202-1,202-2, . . . , 202-N, hereinafter referred to as microphones 202, toprovide analog input signals 116. The analog input signals 116 maysuffer from background noise generated by a noise source. For thepurpose of illustration, the noise source is assumed to be a distantsource relative to the external sources of the analog input signals 116.As a result, the background noise appears as a common mode signal to themicrophones 202. On the other hand, the analog input signals 116 fromthe desired source appears as a differential signal to the microphones202.

The microphones 202 provide the analog input signals 116 to respectiveanalog-to-digital converters (ADC) 204-1, 204-2, . . . , 204-N,hereinafter referred to as ADCs 204. In an embodiment, the microphones202 can be connected in a phase offset geometry to the ADCs 204 withequal group delays. Based on their types, for example, 8-bit or 16-bit,the ADCs 204 process the received analog input signals 116 to providecorresponding noisy digital signals. Further, the noisy digital signalsfrom the ADCs 204 may be combined to provide one noisy digital signal

In one embodiment, the noisy digital signal can be pre-processed forreducing the noise using a system of subtractors and adders, for examplesubtractor 206, and provide a digital signal 108. The digital signal 108may still have background noise. Therefore, the digital signal 108 isfurther processed by the noise removal system 102.

In an embodiment, the noise removal system 102 includes thetransformation module 118, a signal optimizer 208, the threshold filter120, the signal synthesizer 122, and a residue noise module 210. Thetransformation module 118 receives the digital signal 108 in time domainand transforms it into the frequency domain to generate the f-digitalsignal 124 in a manner similar to that discussed above.

As discussed earlier, the total energy of the frequency spectrum isdistributed over the useful bins and the noise bins present in thef-digital signal 124. The noise bins occupy a chunk of the total dynamicheadroom of the f-digital signal 124 and thus, limit signal reliability.Therefore, the noise bins are discarded to concentrate the spectrumenergy on the useful bins such that a reliable signal with high signalpeaks can be realized.

The f-digital signal 124 from the transformation module 118 can be fedto the signal optimizer 208 and to the residue noise module 210. Thesignal optimizer 208 performs a predefined phase correction to thef-digital signal 124 and acts as a preliminary noise remover. Based on aknown profile of the noise signals, the signal optimizer 208 performsnoise removal using signals that correspond to the noise signals, butare phase inverted with respect to the noise signals. The signaloptimizer 208 then purges noise bins based on the known profile of noisesignals and as a result a dynamic headroom is created in the f-digitalsignal 124. As a result, an optimized signal with reduced backgroundnoise is obtained. The signal optimizer 208 can be implemented using avariety of adaptive filters known in the art. Further, the optimizedfrom the signal optimizer 208 is fed to the threshold filter 112.

In an implementation, the residue noise module 210 dynamicallydetermines the threshold profile based on the bins of the f-digitalsignal 124. The threshold profile can correspond to a low level hiss orhum in the f-digital signal 124. In an implementation, the thresholdprofile can be a dynamically calculated amplitude threshold value basedon the bins of the f-digital signal 124. The residue noise module 210provides the determined amplitude threshold value for the f-digitalsignal 124 to the threshold filter 120. The amplitude threshold valuecan be determined by various techniques known in the art.

The parameters used to calculate the amplitude threshold value can beselected based on the level of background noise detected from themicrophones 202. For example, in voice applications where the maximumnumber of useful bins is predictable, the residual noise module 210 cangenerate the amplitude threshold value such that, upon processing, onlythe useful bins are selected by the threshold filter 120 and the otherbins, including the noise bins, are rejected. In another example, for asensor application, the first N bins with maximum amplitude are selectedand rest of the bins are purged. For an ADC precession incrementapplication, the threshold profile is decided by the precession of theADC and the noise bed of the ADC in the pass band. Therefore, in oneimplementation, to increase the precession of an 18-bit ADC to a 20-bitADC, the threshold profile is around 130 db.

In said implementation, the threshold filter 120 receives the optimizedsignal from the signal optimizer 208 and the amplitude threshold valuedetermined by the residue noise module 210. The threshold filter 120further removes noise from the optimized signal, by rejecting thosenoise bins in the f-digital signal 124 that have an amplitude valuebelow the amplitude threshold value, to generate a noiseless signal 126.In effect, high energy signal components are retained and low energynoise portions are discarded from the frequency spectrum of thef-digital signal 124 to provide the noiseless signal 126. The thresholdfilter 120 sends the noiseless signal 126 to the signal synthesizer 122.

The signal synthesizer 122 receives the noiseless signal 126 andfacilitates regeneration of dynamically corrected signal to populate thedynamic headroom created in the signal spectrum. For populating thedynamic headroom, the signal synthesizer 122 provides a gain to thenoiseless signal 126. In one example, the gain is proportional to theenergy in the noise bins that were removed by the threshold filter 120.The signal synthesizer 122 can also increase signal precision or thenumber of bits in the noiseless signal 126.

In an implementation, the signal precision is increased by firstboosting the noiseless signal 126 to recover the dynamic headroom. Inone example, the boost or gain is in proportion to the total energy lostin the bins purged or removed and then based on the desired signalprecision, a few least significant bits are removed to obtain the outputsignal 128 having desired precision. The noiseless signal 126 can berepresented in time domain by using a variety of techniques, such asinverse FFT, inverse DCT, and inverse DWT. The signal synthesizer 122may use substantially high precision twiddle factors in these techniquesfor further increasing the signal precision of the noiseless signal. Forexample, to increase the precision of an ADC from 18 to 20 bits, twiddlefactors corresponding to 24 bits are used.

On account of boosting and conversion of the noiseless signal in thetime domain, i.e., the output signal 128, a minimal noise signal mayremain. However, such a noise signal is insignificant in comparison tothe noise embedded in the received analog input signal 116. In this way,the noise removal system 102 efficiently provides the output signal 128,which is substantially free from the background noise and has a highsignal-to-noise ratio (SNR).

FIGS. 3A, 3B and 3C illustrate frequency spectrums of an analog inputsignal 116 and corresponding frequency spectrums of the output signalobtained after processing by the noise removal system 102 of FIG. 2. Inone example, the analog input signal, such as the analog input signal116, may be a noisy multi-tone signal. FIG. 3A shows a snapshot of thenoisy multi-tone signal in time domain. FIG. 3B represents the frequencyspectrum of the noisy multi-tone signal. The frequency spectrum haspeaks in a few bins corresponding to the multiple tones in themulti-tone signal and low value in several bins corresponding to thenoise signals. FIG. 3C represents a snapshot of the noisy multi-tonesignal in time domain after it is processed by the noise removal system102. As evident from the figure, the background noise in the noisymulti-tone signal has been considerably reduced. Also, the signal energyis improved such that a useful signal occupies the complete dynamicrange. FIG. 3D illustrates an error between a noisy multi-tone signal ofFIG. 3A and the output signal 128 represented in FIG. 3C.

FIG. 4 illustrates the exemplary noise removal system 102 according toyet another embodiment of the subject matter. In one example, the noiseremoval system 102 is a part of an audio processing system 400, such asone used in mobile phones. However, it will be understood that the noiseremoval system 102 can be implemented in a variety of systems used for adiversity of applications. In an implementation, the audio processingsystem 400 includes an analog-to-digital converter (ADC) 402, a dithergenerator 404, an adder 406, and the noise removal system 102.

The ADC 402 samples an analog input signal 116 and, based on theconfiguration of the ADC 402, converts the analog input signal 116 intoa noisy digital signal having a particular number of bits. The noisydigital signal may suffer from quantization noise due to rounding offand truncation of the analog input signal 116 to discrete values duringquantization of the analog input signal 116. In said implementation, adither signal generated by the dither generator 404 can be added to thenoisy digital signal through the adder 406. The dither signal is a noisesignal, for example, a uniformly distributed noise signal, added to thenoisy digital signal in a controlled manner to attenuate leaky spurs toa certain extent. Further, the digital signal 108 is fed to the noiseremoval system 102.

In an embodiment, the noise removal system 102 includes thetransformation module 118, the threshold filter 120, and the signalsynthesizer 122. The transformation module 118 receives the digitalsignal 108 with reduced quantization noise or spurs. The transformationmodule 118 transforms the received digital signal 108 from time domainto frequency domain to determine a frequency spectrum associated withthe digital signal 108 in a manner as explained in the description ofFIGS. 1 and 2. The digital signal 108 represented in the frequencydomain is also referred to as the f-digital signal 124. The f-digitalsignal 124 is fed to the threshold filter 120.

In an implementation, the threshold filter 120 receives the f-digitalsignal 124 and removes the quantization noise from the f-digital signal124 based on a predefined or static threshold profile. A threshold valuein the threshold profile is set depending on the desired outputprecision of the f-digital signal 124, which corresponds to the numberof bits desired in the output signal 128. Higher number of bits may bedesired by an application to increase signal reliability. For example,to achieve a 20-bit desired output signal 128, the noise should be below−130 dB.

The parameters used to calculate the threshold value are selected basedon the intended application and will be well understood by a personskilled in the art. The threshold filter 120 removes the noise binshaving an amplitude below the threshold value in the threshold profileto generate a noiseless signal 126. Therefore, a dynamic headroom iscreated in the signal spectrum of the noiseless signal 126 by removingthe noise bins in the f-digital signal 124. The noiseless signal 126 issent to the signal synthesizer 122.

The signal synthesizer 122 is configured to provide the gain to thenoiseless signal for utilizing the created dynamic headroom. The signalsynthesizer 122 thus generates the noiseless signal 126 in frequencydomain having an increased dynamic range. It is to be noted that thesignal optimizer 208 and the residue noise module 210 are not includedin the present embodiment as the threshold value in the thresholdprofile is fixed and closely linked with the desired precision of theoutput signal 128.

The signal synthesizer 122 transforms the noiseless signal 126 fromfrequency domain to the output signal 128 in time domain as explained inthe description of FIG. 2. Therefore, the noise removal system 102provides the output signal 128 substantially free from the quantizationnoise having a high SNR.

FIGS. 5A, 5B, and 5C illustrate frequency spectrums of the analog inputsignal 116 and the output signal 128 obtained after processing by thenoise removal system 102 of FIG. 4. In one example, the analog inputsignal 116 is an 18-bit leaky tone signal. The frequency spectrumsillustrate conversion of the 18-bit analog input signal 116 into a20-bit output signal 128.

FIG. 5A illustrates the 18-bit leaky tone signal in the frequencydomain. The x-axis represents frequencies of the leaky tone signal,while the y-axis represents amplitude of the leaky tone signal indecibels (dBs). FIG. 5B illustrates a frequency domain plot of thenoiseless signal 126 generated using the noise removal system 102. Thex-axis represents frequencies of the noiseless signal 126, while they-axis represents amplitudes of the noiseless signal 126 in dBs. FIG. 5Crepresents an error plot of the output signal 128 with respect to anideal 20-bit time domain signal.

FIG. 6 illustrates an exemplary method 600 for implementing an exemplarynoise removal system. The exemplary method may be described in thegeneral context of analog and digital circuit elements. However, it willbe noted that the method is also implementable through computerexecutable instructions.

The order in which the method is described is not intended to beconstrued as a limitation, and any number of the described method blockscan be combined in any order to implement the method, or an alternatemethod. Additionally, individual blocks may be deleted from the methodwithout departing from the spirit and scope of the subject matterdescribed herein.

At block 602, an analog input signal is received. For example, the noiseremoval system 102 receives the analog input signals, as described inFIG. 2 and FIG. 4. The analog input signal may suffer from backgroundnoise or quantization noise or both. The analog input signal istypically represented in time domain.

At block 604, the analog input signal is converted into a digitalsignal. For example, the analog input signal 116 is converted into anoisy digital signal by the analog-to-digital converter 112. Further,the noisy digital signal may be pre-processed to remove quantizationnoise by using dither generators and adders. Similarly, the backgroundnoise can be removed by using error microphones and subtractors. Thepre-processed noisy digital signal is referred to as digital signal 108.

At block 606, the digital signal is transformed into frequency domain.For example, the digital signal 108 suffering from noise is fed to thetransformation module 116, which transforms the digital signal 108 fromtime domain to frequency domain. A range of frequency coefficientsassociated with the digital signal 108 are determined. The frequencyspectrum of the transformed digital signal 108 or the f-digital signal124, includes useful bins and noise bins corresponding to the backgroundnoise or the quantization noise or both.

At block 608, a noiseless signal is generated. For example, the noisebins from the f-digital signal 124 are removed based on a thresholdvalue in a threshold profile to generate a noiseless signal. In animplementation, the f-digital signal 124 subsuming the useful bins andthe noise bins can be received by the threshold filter 120. Thethreshold filter 120 attenuates the noise bins in the f-digital signal124 having an amplitude below the threshold value in the thresholdprofile. The threshold profile can be a predefined value or adynamically calculated value. The parameters used to calculate thethreshold value are based on the intended application of the outputsignal 128. The removal of the noise bins from the f-digital signal 124provides the noiseless signal 126. The noiseless signal 126 is generatedwith a dynamic headroom created on account of removal of the noise bins.

At block 610, a gain is provided to the noiseless signal. The noiselesssignal 126 is received by the signal synthesizer 122, which amplifiesthe noiseless signal 126 to effectively populate the created dynamicheadroom. For the purpose, the gain is provided to the signal bins inthe noiseless signal to increase their amplitude. In one example, thegain is in proportion to the total energy lost in purging or removingthe noise bins. As a result, the dynamic range of the noiseless signal126 is improved.

At block 612, the noiseless signal is transformed into time domain. Thesignal synthesizer 122 is configured to transform the noiseless signalfrom frequency domain to time domain. In one implementation, the signalsynthesizer uses substantially high precision twiddle factors to performthe transformation.

Although the exemplary method 600 has been explained with respect to thenoise removal system 102, the disclosed method can be applied on anysimilar noise cancellation systems.

Although embodiments for a system for noise removal have been describedin language specific to structural features and/or methods, it is to beunderstood that the appended claims are not necessarily limited to thespecific features or methods described. Rather, the specific featuresand methods are disclosed as exemplary implementations for the noiseremoval system.

We claim:
 1. A system comprising: a signal unit configured to provide a digital signal; a noise removal system coupled to the signal unit, the noise removal system comprising a transformation module configured to transform the digital signal into an f-digital signal, a threshold filter configured to generate a noise filtered signal from the f-digital signal based on a threshold profile having a single threshold value, a signal synthesizer configured to provide a gain to the noise filtered signal, and transform the noise filtered signal into an output signal, and a noise module configured to determine the threshold profile.
 2. The system as claimed in claim 1, wherein the signal unit comprises: a receiver configured to receive an analog input signal; an analog-to-digital converter configured to generate a noisy digital signal from the analog input signal; and a pre-processing unit configured to process the noisy digital signal.
 3. The system as claimed in claim 2, wherein the pre-processing unit comprises a dither generator configured to add a dither signal to the noisy digital signal for reducing quantization noise.
 4. The system as claimed in claim 2, wherein the pre-processing unit comprises a subtractor configured to deduct background noise from the noisy digital signal.
 5. The system as claimed in claim 1, wherein the signal unit comprises a receiver configured to receive the digital signal.
 6. The system as claimed in claim 1 further comprising a digital signal processor configured to amplify the output signal.
 7. The system as claimed in claim 1, wherein the signal synthesizer is configured to transform the noise filtered signal into the output signal with precision twiddle factors.
 8. The system as claimed in claim 1, wherein the threshold filter is configured to purge one or more noise bins based on the threshold profile.
 9. The system as claimed in claim 8, wherein the threshold value comprises a dynamic amplitude threshold value based on background noise.
 10. The system as claimed in claim 9, wherein the background noise is detected by one or more error microphones.
 11. The system as claimed in claim 8, wherein the threshold value comprises a static amplitude threshold value based on quantization noise.
 12. The system as claimed in claim 11, wherein the threshold value comprises a static amplitude threshold value based on a pre-defined precision of the output signal.
 13. The system as claimed in claim 8, wherein the gain is proportional to the total energy lost in purging the one or more noise bins.
 14. A noise removal system comprising: a transformation module configured to transform a digital signal into an f-digital signal in a frequency domain; a threshold filter configured to remove noise, based on a threshold profile having a single threshold value, from the f-digital signal to generate a noise filtered signal, the removing of the noise leaving a dynamic headroom; a signal synthesizer configured to provide a gain to the noise filtered signal for at least recovering the dynamic headroom, and transform the noise filtered signal into an output signal; and a noise module configured to determine the threshold profile.
 15. The noise removal system as claimed in claim 14, wherein the signal synthesizer is configured to transform the noise filtered signal in a frequency domain into the output signal in time domain.
 16. The noise removal system as claimed in claim 15, wherein the signal synthesizer is configured to transform the noise filtered signal into the output signal using precision twiddle factors.
 17. The noise removal system as claimed in claim 14 further comprising a residue noise module to dynamically determine the threshold profile.
 18. The noise removal system as claimed in claim 14, wherein the threshold filter is configured to remove the noise by purging at least one noise bin below the threshold profile.
 19. The noise removal system as claimed in claim 14, wherein the threshold value comprises a dynamic amplitude threshold value based on background noise.
 20. The noise removal system as claimed in claim 14, wherein the threshold value comprises a static amplitude threshold value based on a pre-defined precision of the output signal.
 21. The noise removal system as claimed in claim 14 further comprising a signal optimizer configured to optimize the f-digital signal.
 22. The noise removal system as claimed in claim 14, wherein the gain is proportional to the noise removed by the threshold filter.
 23. A method comprising: transforming a digital signal to an f-digital signal; generating a noise filtered signal, based on a threshold profile having a single amplitude threshold value, from the f-digital signal; providing a gain to the noise filtered signal to recover a dynamic headroom, the dynamic headroom being created due to generation of the noise filtered signal, and transforming the noise filtered signal into an output signal; and determining the threshold profile in a noise module.
 24. The method as claimed in claim 23, wherein the generating of the noise filtered signal comprises purging noise bins corresponding to at least one of background noise and quantization noise.
 25. The method as claimed in claim 23 further comprising: receiving an audio input signal from an external source; converting the audio input signal into a noisy digital signal; and pre-processing the noisy digital signal.
 26. The method as claimed in claim 25, wherein the pre-processing comprises adding a dither signal to the noisy digital signal to minimize quantization noise.
 27. The method as claimed in claim 25, wherein the pre-processing comprises deducting background noise from the noisy digital signal.
 28. The method as claimed in claim 27, wherein the pre-processing comprises determining the background noise using at least one error microphone.
 29. The method as claimed in claim 23 further comprising synthesizing the output signal from the noise filtered signal using precision twiddle factors. 